DIGITAL OFFERS PERSONALIZATION

Product Leader @ McDonald's

PROBLEM

Only 20% of active mobile application users were using digital offers. Offers were too general and lacked efficiency as a customer incentive mechanism.

Marketing spent too much time on customer exploration to find the best offering schema. There were no automation and data analysis tools that would help quickly generate offers based on customer ordering history.

SOLUTION

An in-house customer data platform paired with a third-party personalization engine for tailored offering suggestions.

PRODUCT TYPE: mobile app, infrastructure service

TARGET AUDIENCE: internal teams (direct), general consumers (indirect)

TEAM

3 outsourced feature teams
Core team size: 19 people
Overall team line-up: project manager, designer, system analysts, back-end developers, mobile developers, QA engineers, DevOps engineers

STACK

Native mobile application
Microservice architecture
Customer data platform
Third-party personalization engine
Python, Kotlin, Swift
Hadoop
REST APIs

MY CONTRIBUTION

Defined use cases and requirements
Performed interactions with stakeholders
Led the development cycles for 3 teams
Handled prioritization and resource balancing
Performed a vendor selection process
Led integration with the third-party vendor

MY ACHIEVEMENTS

Increased effectiveness of offer targeting by 50%
Deepen the capabilities of customer data analysis with user segmentation and triggering mechanics
Decreased the load on a marketing team by automating routine operations and insights exploration

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